How to run an LLM on your laptop

MIT Technology Review - AI
Jul 17, 2025 17:01
Grace Huckins
1 views
airesearchtechnology

Summary

The article explains how individuals can run open-weight large language models (LLMs) locally on their laptops using downloadable models stored on a USB stick, as demonstrated by Simon Willison. This approach empowers users with greater control and privacy, highlighting a shift toward more accessible and decentralized AI tools outside of major tech platforms.

MIT Technology Review’s How To series helps you get things done. Simon Willison has a plan for the end of the world. It’s a USB stick, onto which he has loaded a couple of his favorite open-weight LLMs—models that have been shared publicly by their creators and that can, in principle, be downloaded and run…

Related Articles

PEPE Price Projection: $0.00005 by 2025 as Ozak AI Rockets to New Highs

Analytics InsightJul 17

The article discusses the projected rise of PEPE's price to $0.00005 by 2025, highlighting growing investor interest in AI-driven cryptocurrencies. It also notes that Ozak AI has reached new performance highs, signaling increased momentum and innovation in the AI sector. These trends suggest that AI integration is playing a significant role in shaping the future of digital assets and investment strategies.

Don't Fall for AI: Reasons for Writers to Reject Slop

Hacker News - AIJul 17

The article argues that writers should reject low-quality, AI-generated content ("slop") because it often lacks originality, depth, and emotional resonance. It warns that widespread use of such content could degrade creative standards and undermine the value of human authorship. This highlights ongoing concerns in the AI field about balancing technological advancement with the preservation of authentic, high-quality writing.

A £3.93/mo Nomad‑backed learning lab: Next.js · .NET · Postgres on a budget

Hacker News - AIJul 17

The article details how to set up a cost-effective learning lab for web development technologies like Next.js, .NET, and Postgres using Nomad, all for just £3.93 per month. While not directly focused on AI, this affordable infrastructure can support AI experimentation and learning by providing accessible backend resources for developers and students. The approach highlights the growing accessibility of robust development environments, which can accelerate AI prototyping and education.